Field
This disclosure is generally related to person identification, and more specifically to methods and systems for identifying persons using ocular biometric information.
Description of the Related Art
Accurate, non-intrusive, and fraud-resistant identity recognition is an area of increasing concern in today's networked world, with the need for security set against the goal of easy access. Many commonly used methods for identity determination have known problems. For example, password verification has demonstrated many weaknesses in areas of accuracy (the individual typing the password may not actually be its owner), usability (people forget passwords), and security (people write passwords down or create easy-to-hack passwords).
The communication between a human and a computer frequently begins with an authentication request. During this initial phase of interaction a user supplies a system with verification of his/her identity, frequently given in the form of a typed password, graphically encoded security phrase, or a biometric token such as an iris scan or fingerprint. In cases when the user is prompted to select the identification key from a sequence of numerical and graphical symbols, there is a danger of accidental or intentional shoulder surfing performed directly or by use of a hidden camera. Moreover, such challenges may become specifically pronounced in cases of multi-user environments including shared-workstation use and more contemporary interaction media such as tabletops. Authentication methods requiring remembrance of information such as symbols and photos have reduced usability, due to the fact that long, sophisticated passwords can be easily forgotten and short passwords are easy to break. Even biometric methods such as iris and finger print-based authentication may not be completely fraud-proof, since they are based on a human's body characteristics that can be replicated.
There are a number of methods employed today for biometric purposes. Some examples include the use of fingerprints, iris, retina scans, face recognition, hand/finger geometry, brain waves, periocular features, ear shape, gait, and voice recognition. Iris-based identification is considered to be one of the most accurate among existing biometric modalities. However, commercial iris-identification systems may be easy to spoof, and they are also inconvenient and intrusive since they usually require a user to stand very still and very close to the image capturing device.
The human eye includes several anatomical components that make up the oculomotor plant (OP). These components include the eye globe and its surrounding tissues, ligaments, six extraocular muscles (EOMs) each containing thin and thick filaments, tendon-like components, various tissues and liquids.
The brain sends a neuronal control signal to three pairs of extraocular muscles, enabling the visual system to collect information from the visual surround. As a result of this signal, the eye rotates in its socket, exhibiting eye movement such as the following types: fixation, saccade, smooth pursuit, optokinetic reflex, vestibulo-ocular reflex, and vergence. In a simplified scenario, when a stationary person views a two-dimensional display (e.g., computer screen), three eye movement types are exhibited: fixations (maintaining the eye directed on the stationary object of interest), saccades (rapid eye rotations between points of fixation with velocities reaching 700°/s), and smooth pursuit (movements that occur when eyes are tracking a smooth moving object).
Accurate estimation of oculomotor plant characteristics is challenging due to the secluded nature of the corresponding anatomical components, which relies on indirect estimation and includes noise and inaccuracies associated with the eye tracking equipment, and also relies on effective classification and filtering of the eye movement signal.
In some cases, an intruder may carry out a coercion attack in which a genuine user is forced to log into a secure terminal (e.g., using a remote connection) under duress. Some approaches for preventing coercive attacks are easily observable (for example, typed passwords or voice commands), or intrusive (for example, skin conductance sensors).
Many biometric technologies are susceptible to attacks in which faked human features (for example, fake fingerprints, facial images, or iris images) are successfully as passed off as authentic. For example, some commercial iris-identification systems can be spoofed by high resolution images printed on placards with small holes in the images to bypass liveness tests, fingerprints can be spoofed with common household articles such as gelatin, and face recognition systems can be spoofed with printed face images. In certain cases, a spoofing attack involves presenting an accurate mechanical replica of the human eye is presented to the sensor. Such replicas may perform the eye movements similar to that of a human.